Conventional medical laboratory systems contain many segments for processing patient samples, some of which are automated and some of which require manual operation. Laboratory systems today have become more efficient due to those segments which have become automated. However, there are still several components of medical laboratory systems that can be automated in order to reduce the time it takes for an analysis of a sample, reduce the need for manual operation of the system, and reduce the space required by machinery.
Generally, the laboratory process can be organized into four phases: association, pre-analytical, analytical, and post-analytical. These four phases typically occur within any laboratory process. However, some conventional labs may have a process that uses standalone units throughout the lab while others may connect some of the units with a conveyance system to move the sample from unit to unit. These two styles have some common and some different processing needs. Additionally, some conventional labs may consistently process the same types of sample tubes (e.g., as in those from a kit) while others may have a wide range of tube types they must accommodate. Furthermore, many labs may have a preference for a particular manufacturer of an analyzer while others may use all of the analyzers from one manufacturer.
Thus, there is a need for a more efficient system and method for processing patient samples that can accommodate both a process using standalone units and units connected with a conveyance system, a variety of sample tube types, and analyzers from any manufacturer.
One aspect of automated laboratory systems relates to tube identification. Automatic tube identification is needed in a laboratory system so that the laboratory system knows how to process samples in the sample tubes.
Conventional tube-in-rack detection typically utilizes image analysis tools on 2-dimensional images acquired by one camera or a plurality of cameras in order to determine objects in the field of view of the cameras. This technology is well known in various fields, including, e.g., the analysis of pathology samples by microscopes.
In other fields, this technology may be used to identify objects in moveable loading or unloading means of a system, including, e.g., identifying drawers of a workbench. See, e.g., WO/2010/017528. A series of images can be taken by each camera during the opening and closing of the drawer and stitched together to generate an overview image. Within this overview image, single objects can be detected by image analysis.
In the field of laboratory automation systems, it is well known that single objects, such as a cap or closure of a sample tube, located in a holding rack can be identified by employing image analysis algorithms on top views of the hold racks. However, the image analysis algorithms are typically limited to the identification of only the single object and do not identify other details of the objects within the image.
Other tube identification mechanisms include the use of sample tube markers. Conventional sample tube markers used to identify a sample tube requiring immediate analysis typically include self-adhering labels (e.g., colored labels indicating urgency), “urgent” stickers, or simply a handwritten note indicating urgency on already existing labels. These urgent sample tube markers are inefficient and non-automated, requiring a laboratory technician to apply and/or handwrite the indication of urgency.
Additionally, conventional sample tube markers used to identify a centrifuged sample may include g-force sensitive labels. These labels measure whether there was an impermissibly high shock during transport. However, such labels are on the side of sample tubes, and as such cannot be easily reviewed or identified by overhead cameras and the like.
Embodiments of the invention address these and other problems, individually and collectively.